Our core technologies have been created from the ground-up to simultaneously deliver interpretability and state-of-the-art performance. Our focus on interpretability means:
Built on the foundation of our core technologies, we deliver interpretable and performant end-to-end solutions for business problems. Some examples of these solutions include:
Dimitris is a Co-Founding Partner of Interpretable AI and the Co-Director of the Operations Research Center at MIT. He has received numerous research awards, has written over 200 research papers and 4 graduate textbooks that are used around the world. He was a Co-Founder of Dynamic Ideas LLC, the assets of which were sold to American Express in 2002.
Jack is a Co-Founding Partner of Interpretable AI. He has developed many novel analytics approaches including the Optimal Trees methodology, and has considerable experience applying machine learning and AI to problems in both research and industry settings. He has a PhD in Operations Research from MIT.
Daisy is a Co-Founding Partner of Interpretable AI. She has expertise in developing scalable machine learning techniques including Optimal Imputations, with extensive research and industry experience in applications of analytics and AI systems in health care. She has a PhD in Operations Research from MIT.
Jeremy is a Research Scientist at Interpretable AI. He is passionate about applying state-of-the-art technology to real-world problems and has deep expertise in natural language processing. He holds a Master of Business Analytics from MIT and a MS in Applied Mathematics from École Centrale Paris.
Maxime is a Research Scientist at Interpretable AI. He leverages his expertise in machine learning to drive value for organizations, with extensive experience in the latest deep learning developments. He studied data science during his master's at MIT and holds a MS in Applied Mathematics from École Centrale Paris.